As is well known, there are video techniques for indicating moving objects from a stationary platform that operate by simply subtracting from the amplitude of each pixel of a current video image frame, the amplitude of that pixel of a stored preceding video image frame that corresponds thereto. This results in the substantial removal of those pixels of the video image pixels that define stationary objects. Digital image processing techniques which may be employed in this frame difference approach are disclosed in U.S. Pat. No. 4,692,806, which issued on Sep. 8, 1987, and in the Anderson et al. article "Change Detection and Tracking Using Pyramid Transform Techniques", SPIE Conference on Intelligent Robotics and Computer Vision, Boston Mass., 1985, SPIE Vol. 579, both of which are incorporated herein by reference.
Also incorporated herein by reference is the disclosure of the Burt et al. article "Object tracking with a moving camera, an application of dynamic motion analysis", IEEE Workshop on Visual Motion, Irvine Calif., March 1989, if the camera is moving, which teaches that it is often possible to compensate for the resulting image motion by electronically shifting and rotating successive image flames to achieve alignment prior to computing a frame difference. Such electronic alignment is based on a simple image warp (e.g., based on an affine transform) that is effective when scene motion contains relatively little parallax, such as when the camera is rotating, but not translating, or when objects within the region of the camera's field of view for which alignment is performed occur in a relatively narrow range of depths.
Further incorporated herein by reference is the disclosure of the Hanna article "Direct multi-resolution estimation of ego-motion and structure from motion", IEEE Workshop on Visual Motion, Princeton N.J., October 1991, which teaches that electronic alignment can be generalized to compensate for parallax motion by including an image processing step that recovers an estimate of the distance to objects in a scene based on the observed motion. The estimated distance along with estimates of the camera's own motion are then used to predict and compensate for parallax motion.
The existing image processing techniques for depth recovery and parallax compensation have possible practical limitations. These image processing techniques are costly to compute. In addition, they can make significant errors in depth estimates along the boundaries between nearby and more distance objects in the image.
The video technique of the present invention is directed to overcoming such problems.